A new method for muscle fatigue assessment: Online model identification techniques. Issue 4 (5th August 2014)

• Record Type: Journal Article
• Authors: Papaiordanidou, Maria; Hayashibe, Mitsuhiro; Varray, Alain; Fattal, Charles; Guiraud, David
• Is Part Of: Muscle & nerve. Volume 50:Issue 4(2014:Oct.)
• Page Start: 556
• Page End: 563
• Publication Date: 2014-08-05
• Subjects: Neuromuscular diseases -- Periodicals; Muscles -- Periodicals; Nerves -- Periodicals; 616.74
• DOI: 10.1002/mus.24190
• Languages: English
• ISSNs: 0148-639X

Abstract

<abstract abstract-type="main"> <title>ABSTRACT</title> <p> <italic>Introduction</italic>: The purpose of this study was to propose a method that allows extraction of the current muscle state under electrically induced fatigue. <italic>Methods</italic>: The triceps surae muscle of 5 subjects paralyzed by spinal cord injury was fatigued by intermittent electrical stimulation (5 × 5 trains at 30 H<sc>z</sc>). Classical fatigue indices representing muscle contractile properties [peak twitch (Pt) and half‐relaxation time (HRT)] were assessed before and after each 5‐train series and were used to identify 2 relevant parameters (<italic>F_m</italic>, <italic>U_r</italic>) of a previously developed mathematical model using the Sigma‐Point Kalman Filter. <italic>Results</italic>: Pt declined significantly during the protocol, whereas HRT remained unchanged. Identification of the model parameters with experimental data yielded a model‐based fatigue assessment that gave a more stable evaluation of fatigue than classical parameters. <italic>Conclusions</italic>: This work reinforces clinical research by providing a tool that clinicians can use to monitor fatigue development during stimulation. <italic>Muscle Nerve</italic> 50: 556–563, 2014</p> </abstract>